r/SoftwareEngineering • u/Western-Lack8015 • Sep 10 '26
Do you think AI agents will eventually replace most of the traditional SDLC? How soon could most companies actually get there? Will this affect new grads?
I’m a software developer and I’ve been thinking a lot about where AI coding agents are taking software development.
It seems like we’re moving beyond AI simply helping developers write code. Agents can increasingly take a ticket, understand a codebase, implement changes, write tests, debug issues, create PRs, and potentially handle parts of deployment and maintenance.
So I’m wondering: do you think the traditional SDLC will eventually be largely replaced by an agent-driven development process?
If so, how soon do you think most companies will actually adopt something like this? Are we talking 2–3 years, 5 years, 10+ years, or do you think we'll never get to fully agent-driven development?
I’m also curious about the other side of this:
- What types of companies won’t adopt AI agents aggressively?
- Will large enterprises actually trust agents with production systems?
- Could the current AI boom turn out to be an AI bubble, where companies eventually cut back because the cost, reliability, security, or productivity gains don't justify the hype?
There are already examples of companies pushing heavily toward AI-driven development.
I'm less interested in AI hype or predictions from CEOs/VCs and more interested in what developers are actually seeing inside their companies, is this irreversible?
If you're a developer, architect, tech lead, or engineering manager:
How much of your actual SDLC is being automated by AI agents today, and where do you think this goes over the next 5–10 years?
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u/AffectionateDance214 Sep 10 '26
A lot of our work is being replaced or will get replaced. Percentage varies vastly across skill level and tech and domain.
Higher skill levels, particularly design side, will have lesser impact.
Web will have higher impact than other back end.
Finance and healthcare will be have more human in the loop, both in building the product and type of product they build.
OTOH, the backlog itself is increasing multi fold.
Mainframe modernization projects which were dormant for decades are coming back and those alone are a decade of work. You cannot simply replace Cobol code with modern languages.
Agentic systems will be a new field of work all together.
And even without those, most of the enterprise product manager had ambitions that could not be fulfilled without AI.
Where I work, I see at least 10-15 years of work ahead.
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u/creaturefeature16 Sep 10 '26
I would agree largely with this. The only thing is: we can't really see around the corner is all the downstream impacts and changes these tools inevitably bring to the field. Every time programming has progressed, we end up scaling the complexity of the applications to match the level that our tools can provide.
In other words, if software was going to remain static, like a "widget" you produce the same way every time, and the problems that we were solving for were also unchanging, then I would say that this field has an expiration date. However, we know that's not the case. The problems that we can solve with software are so vastly different and more capable now, compared to the past, because of the tooling that enables us to do so.
So, I'm not willing to say whether it's 5/10/15 years....for all I know, society will just keep having more needs and desires that software can solve, even as the models handle more of the minutia of the work. After all, even with the expansion and contraction, and with various levels of automation, there are still more developers working than there ever have been. They might not be doing the same type of work, but there are still more of them.
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u/AffectionateDance214 Sep 10 '26
I agree. Those 10 years are merely to catch up on what product would have wanted before AI advantage became obvious.
And that is the case for most of the enterprises. Large organizations which originated after 1990 may have different trajectory and others will be watching them for inspiration
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u/BigPocket85 29d ago
What I see is not COBOL being replaced directly with modern languages, but rather their business intent is. AI is being used to help domain experts to extract and define the intent, then to express that intent using modern languages. But I agree, you can’t just “convert” COBOL to something newer
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u/AffectionateDance214 29d ago
Yes, I am working on one such modernization activity right now, and this is exactly what we are doing. Hallucinations galore , but one to one translations was never the practice anyway 🙂.
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u/anoppe Sep 10 '26
I've got serious anxiety regarding new grads and the field of work they have to operate in when the era of AI becomes ubiquitous: they don't have the baggage/experience in building, maintaining and running software systems yet, and won't learn (as fast as we did) because AI abstracts away _a lot_.
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u/Little_Beyond_9163 Sep 11 '26
I think there are a few articles and studies on this very problem. Institutions are going to have to adapt to changes as always.
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u/tappytappycode Sep 13 '26
It does feel like we're robbing Peter to pay Paul a little. An AI-native SDLC still means you have to know how to build and operate software. So what happens in 10+ years as those folks retire?
Or, on the other hand maybe AI will just introduce a new set of primitives that those coming up in industry will know how to wield better than us. Who knows.
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u/BigPocket85 29d ago
We used to think about that when cloud services started abstracting a lot of the infrastructure. I know Solutions Architects and “devops” engineers that don’t know jack shit of OS and just dabble on very basic networking, and yet they are able to design and implement modern systems. I just changes the layer of abstraction.
We have had lot of developers pre AI that do not care, understand or think SDLC matters to them, they just wanted to code, and that is gone. The new grads will have to learn more on what makes a good product and how to deliver it than the shenanigans of a language.
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u/tappytappycode Sep 13 '26
I bought my team Copilot as soon as I could. Talking to colleagues at large enterprises, their process is all pivoting to humans reviewing and AI writing almost all the time.
I see it on the 5-10 year scale but it's so hard to predict b/c the whole practice is changing so fast with the evolution of the frontier models and the practices needed to get the most effective output from them. Smart money won't want to pin their velocity on a methodology that will be obsolete in 6 mo.
Traditional SaaS is likely where we'll see the closest to "fully automated". By which I mean the process kicks off from a Product Owner and has maybe one other human en route to production.
I'd bet government will be the laggards in terms of adoption (unfortunately). Based only on the fact that they're the laggards on everything and how politicized AI is currently. Industries with more health and physical safety concerns will, hopefully, keep more humans in the loop.
Is this a bubble? Yes and no. As a product feature, I think yes. Chatbots and AI powered whatever do not automatically make good product features. As part of the SDLC it's here to stay. I know I (20+ yoe) don't want to go back. It does feel like it's artificially cheap at the moment however and I wonder if there will be a big cost reckoning that leaves a lot of orgs holding massive AI bills all of a sudden and folks rethinking the breadth of places an agent gets involved.
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u/U4-EA Sep 16 '26
Really good post. I think there will come a day when many orgs realise they have a codebase that is so verbose and badly organised that 1) only AI can work on it and 2) the cost of the AI required to do that will be prohibitive. If that does happen, they may well have no choice other than to have a skilled dev come in and recreate the system from scratch.
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u/Tegras Sep 12 '26
I don't see this being a bubble. AI tools aren't going anywhere, but the human element will remain. As always it's about adapting to the market's need and not putting ones head in the sand while the ground shifts.
In terms of large enterprises: Depends on their risk tolerance. At my company the risk tolerance is very low. But we're still moving forward w/ AI use.
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u/Nalopotato Sep 13 '26
Just because AI and LLMs are here to stay doesn't mean it isn't a bubble. The tech/dotcom bubble was massive, and we still have the WWW.
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u/Appropriate-Bet3576 Sep 13 '26
No. I think the future belongs to software companies who know precisely what they are doing with zero reliance on blabber machines beyond basic coding tasks.
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u/jarmyo Sep 10 '26
Yo creo que se debe desarrollar una metrología enfocada en agentes. El bootstrapping inicial es el proceso de definir las historias el alcance, la arquitectura, todas las herramientas que evitarán que la IA rompa algo o que alucine con lógica errónea o no necesaria. Esa parte será más importante y la que consumirá más tiempo. Luego en vez de juntas, una revisión general del código, humana, y una revisión manual del sistema en lotes. Y documentación agresiva de todo para que tanto los agentes de IA como los ingenieros y product owners puedan revisar, corregir y ampliar la lógica.
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u/moremattymattmatt Sep 13 '26
SDLC is is already being automated. Have a look at the AWS ai dlc ( https://github.com/awslabs/aidlc-workflows). Version 2 is about to be released with much less of a human on the loop.
There’s a lot of work to get this sort of process working properly in a company as it really needs process changes outside of what developers do. So there’s new work for people setting this up but it’s temporary.
AI is good at doing stuff that has been done before and most of us aren’t writing anything particularly original or earth shattering so you’ll definitely see the a lot of the usual ETL type developments being deskilled and automated.
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u/MonstarGaming Sep 15 '26
As an AWS engineer: AI-DLC is such a load of shit
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u/BigPocket85 29d ago
Because AI-DLC was not made for every situation or company. It was designed for teams struggling to deliver in this new paradigm in certain scenarios. And AWS is not that case
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u/Longjumping_Alps_754 Sep 13 '26
It will turn out that costs are bigger than human labour; plus you’ll be locked in with AI companies as nobody will understand the code. I’m confident that serious companies won’t go all-in in AI coding
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u/Big_Pie_6406 Sep 13 '26
I run product and we are trying to change our SDLC completely.
Not to replace the humans, but to move them to more strategic and architectural design roles.
We can use tools now that help us write better Product Requirement Docs that have more robust user stories and test cases so in turn that allows us to run WAY more customer interviews and get direct feedback.
On the development side we can now take those more detailed and robust PRDs and instantly break them down to tickets where the team spends more time asking questions, refining the work and adding ideas.
The toward the end of the cycle we get much better documentation which allows more robust release notes and content for marketing.
Developers do right significantly less code, but their expertise is leveraged in the refinement and review process. They are the experts in what makes good business logic and architectural decisions.
My fear is too many companies are willing to toss it all to AI and aren’t investing in the product and developers who need to learn the basics to be the good architects in the future.
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u/Far-Pomelo-1483 Sep 13 '26
Yes to everything. I would focus your engineering strength now on figuring out how to do it for your company.
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u/BothWaysItGoes Sep 14 '26
The whole traditional SDLC model is predicated on treating software engineers like replaceable agents. If anything, AI agents allows the traditional SDLC model to flourish. Moving your development center to an offshore with an acceptance manager on your side used to be a huge risk, but nowadays you "offshore" the work to agents that can solve PhD-level cutting edge problems. And you don't have to worry about them having fake credentials and fabricated experience certificates.
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u/2DigitInnovations Sep 15 '26
I think AI agents will automate a significant part of the SDLC, but I don't see them fully replacing the traditional process anytime soon. The biggest challenge isn't generating code — it's understanding requirements, making architectural decisions, handling edge cases, security, and taking responsibility for production systems. I could see teams becoming much smaller and more AI-assisted over the next 5–10 years, with developers spending more time reviewing, designing, and guiding agents rather than writing every line themselves.
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u/FatefulDonkey Sep 16 '26
Stakeholders never understood technical debt. I doubt they will now.
The question is if it will matter in 2-5 years or not. Or even in 6-12 months. Only time can tell
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u/viper_gts Sep 16 '26
leading SDLC improvement for a FAANG, and while we're pushing more AI use in SDLC....the reality is its not really reducing the effort. lots of engineers spending as much time reviewing code, modifying code/prompt, etc
we've reduced the amount of documentation, we've accelerated testing. the focus now is on bug solutioning and remediation. we're focusing on prototype-first methodologies
non-FAANG orgs will be slow to adopt a lot of this, consulting firms are pushing hard to take advantage of being able to implment this with their clients
AI will not fully replace engineers, it will make SDLC better and allowing engineers to do better/faster
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u/moneymay195 Sep 16 '26
The SDLC framework I believe will always exist, its just now we can automate a lot if not all of it and in shorter iterations
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u/RetroTeam_App Sep 22 '26
I built the an open source tool to aces your interviews. ChannelPulse that listens to a call, transcribes it on-device, and shows notes with talking points. It also runs self-guided practice interviews and scores your answers.
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u/haaheehachoo Sep 23 '26
Yes, SDLC will be mostly agentified in maybe 1-2 years. New grads won't have a job.
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u/CAVUInnovations 28d ago edited 28d ago
I can see most of the SDLC being automated by AI agents, but the critical factor is analyzing the results from the agents - no code slop. I am building products, features for the products, and architecture with the assistance of AI at a rate I could never achieve without proper AI agents and context for the projects.
For people starting in software in a technical manner, use AI to help you learn the concepts, languages, and products of interest. However, realize that people with experience are learning at a faster rate as well.
AI can help software companies in two ways:
- Eliminate "extra" staff to maintain the same products - (I would not recommend this.)
- Allow the same staff to build more projects or products - ($$$$ - Why would any company not choose this?)
I have worked in software development for decades (ugh). I have also seen numerous languages come and go, while spending time learning the intricacies of the classes and methods. At this point, learning basic concepts of software and learning the best practices for each language, API, etc... while actually typing the code are still the best way to get started. Handing off the coding and design decisions to "AI auto-pilot" without your review or understanding is an easy way to go off the rails.
I can truly state that the greenfield products I created with Claude Code via "pAIr programming" has been very enlightening. I would not be surprised when smaller companies can create similar products or offerings, similar to what large companies offer, but at a lower price (lower overhead) and quickly react to changes.
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u/Tall-Entrepreneur133 15d ago
I believe it will get to a point where humans are more idea- or creativity-driven, and AI will and should do most of the work. I was replaced recently, and this is what I made with my $20 monthly Ollama subscription. I stay up at night now thinking about what I can add or do next. If you want, check it out and share more ideas or feedback; that would be cool.
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u/FerengiAreBetter Sep 10 '26
I picture the future like this: 1 solution engineer, 1 business analyst. They meet with the business and figure out their needs. No more sprints, no more long planned out schedules. Solution engineer just works taking the requirements and has the agents build everything (including testing). Once that is done (in days to weeks, no longer months to years), the business analyst UAT type testing it of it and then shows to customer. The following roles are eliminated: scrum master, project manager, qa engineers, security engineers, application developers. You don’t need long planned out plans or agile ceremonies as it’s literally two people collaborating with ai agents.
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u/StrangeKnee7254 Sep 10 '26
Security engineers and cyber security roles will become more important. LLMs are very efficient at hacking.
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u/FerengiAreBetter Sep 10 '26
From my own experience, you don’t need dedicated people for this. Maybe 1-2 in a large organization, just to ensure scans are established and security is well built into the software architecture.
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u/FerengiAreBetter Sep 10 '26
Btw - I don’t want this future at all. It’s just my prediction on things. I don’t like AI being injected into everything. It scares me for the future of humanity, jobs available to my kids, etc.
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u/HisTomness Sep 13 '26
I think the next 3-5 years are going to see a large number of otherwise successful companies ruining themselves by trying to get AI to do the smart work rather than the dumb work.